Vented versus non-vented Petri dishes

Vented Petri dishes have a small lip on the top edge of the dish that allows the lid to sit a little up from the bottom, allowing for some air flow.  Non-vented Petri dishes allow the lid to sit more or less flat on the bottom.  I was wondering what the best applications are for triple, single and non-vented Petri dishes, and found this guide from Thomas Scientific:

  • Triple vented: aids gaseous exchange. Ideally suited for short term work
  • Single vented: limits gaseous exchange, minimizes evaporation and dehydration. Ideally suited for long term work
  • Non-vented: most suitable for anaerobic and long term work
Non-vented Petri dish
Vented Petri dish

JMP report file .jrp file to csv

Here’s a quick and dirty Perl script to get a data table out of a .jrp file from JMP.  Not guaranteed to work for all files, as I’ve only tested it on one (so modification may be necessary).

#! /usr/bin/perl -w

use strict;
use Getopt::Long;
my $jmp_file;
my $colhead;
my $values;
my $row;
my @records;
my $ndata; 
GetOptions ('jmp=s' => \$jmp_file) or die("Error in arguments\n");

open (JMP,"<$jmp_file") || die "cannot open JMP input file $jmp_file";
if($_=~/New Column\(\s\"(.+?)\",.+$/){ # Get column names
if($_=~/Set Values\(\s[\[\{](.+?)[\]\}] \) \),/){ # Get row values
my @row = split ", ", $values;
unshift @row, $colhead;
$ndata= scalar @row;
push @records, \@row;

# Rotate table 90 degrees (rows-to-columns)
my $nrecords=scalar @records;
for(my $i=0;$i<$ndata; $i++){
for(my $j=0;$j<$nrecords;$j++){
print "$records[$j][$i]";
print "," if $j<($nrecords-1) 
print "\n";

Find homopolymeric tracts in a FASTA genome

Assuming standard FASTA format, this BASH one-liner finds homopolymeric tracts (HTs, stretches of the genome where a single nucleotide is repeated many times, e.g. AAAA or TTTTTTT) in a genome and outputs the region.  Such regions are prone to sequencing errors, but are also mutational hotspots as they are susceptible to slippage errors during replication and transcription. Some evidence suggests that HTs may have a regulatory role in prokaryotes.

tail -n+2 GENOME.fa | tr -d '\n' | grep -ob -E "(\w)\1{4,}" | sed 's/:/\t/g' | awk '{print $1+1"\t"$1+length($2)"\t"substr($2,0,1)"\t"length($2); }' | sort -k1n


# strip the FASTA header
tail -n+2 GENOME.fa
# remove newlines
tr -d '\n'
# match >4 (i.e. 5 or more) of the same character, output the match and byte offset
grep -ob -E "(\w)\1{4,}"
# replace the ":" added by grep with a tab
sed 's/:/\t/g'
# prints the genomic position (start + end) of the HT, nucleotide (ACGT) and the length of the tract
awk '{print $1+1"\t"$1+length($2)"\t"substr($2,0,1)"\t"length($2); }'
# sorts by natural numeric position in the genome
sort -k1n

Example output (Pseudomonas fluorescens Pf0-1 NC_007492.2):
35 39 C 5
157 162 A 6
374 378 C 5
440 444 T 5
529 533 T 5
1432 1436 T 5
3304 3308 C 5
3310 3315 C 6
3626 3630 G 5
4063 4067 G 5


I wrote a quick Perl script to visualize SNPs in a gene from experimental evolution sequencing data.  Useful for making figures when one gene is hit by mutations in multiple lineages.  It outputs an SVG file with the reference sequence and the changes.

For the moment, it only visualizes substitutions, not insertions/deletions or anything more exotic.  More to come.

Example: SNPs found in Pseudomonas aeruginosa gene PA2449 (converted to PNG)


(Thanks to Sofia Robb for teaching Perl as part of Programming for Evolutionary Biology!)

Download SNPsvg here.